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Record W2176674897 · doi:10.1139/x11-029

Tree growth and disturbance dynamics in old-growth subalpine spruce forests of the Western Carpathians

2011· article· en· W2176674897 on OpenAlexvenueno aff
Janusz Szewczyk, Jerzy Szwagrzyk, Elżbieta Muter

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsPicea abiesMontane ecologySubalpine forestKarstDisturbance (geology)Bark beetleForest dynamicsDendrochronologyEcologyGeographyTree lineBark (sound)Stand developmentForestryBiologyClimate change

Abstract

fetched live from OpenAlex

Are the dynamics of natural subalpine spruce ( Picea abies (L.) Karst.) forests of central Europe governed by stand-replacing disturbances caused mostly by winds or by moderate disturbances resulting from bark beetle outbreaks? We analyzed tree-ring series from subalpine spruce forests in two mountain ranges of the Western Carpathians to determine the frequency and severity of disturbances and their effects on tree recruitment. The boundary-line method was employed to identify significant growth releases, interpreted as results of disturbances. In both study areas, major releases were not numerous but were regularly distributed over time. We found no evidence for stand-replacing disturbances. This result contrasts sharply with earlier findings from the Western Carpathians. The age structure of the forests studied indicates that the amount of tree recruitment was greater 150–200 years ago than in the subsequent 150 years. Our results suggest that stand dynamics in the forests analyzed are driven by numerous events of limited spatial extent and that stand-replacing disturbances are not necessary for the development of unimodal age structure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.256
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations47
Published2011
Admission routes1
Has abstractyes

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